Raman spectroscopy is a powerful technique for rapid, non-invasive and reagentless analysis of materials, including biological cells and tissues. There has long been interest in applying Raman spectroscopy to biological tissues in general and breast cancer samples in particular. Raman spectroscopy and imaging are molecular diagnostic techniques that have demonstrated promise for detection of pathogens. In the area of biothreat detection and identification, Raman spectroscopy provides specific molecular information that is essential for an accurate assessment of potential biothreats. Automation of spectral acquisition is a critical step in the implementation of a new, important class of continuous, on-line detection strategies that will increase reproducibility and speed of biothreat detection.
Acquiring a Raman spectrum involves exciting the vibrational states of molecules using light, and recording light scattered from the molecules during this process. A Raman spectrum indicates the relative intensity of the excitation of molecular vibrations by recording the amount of light scattered from molecules as a function of energy shift from the exciting illumination. The pattern of a Raman spectrum is determined by the structure of the molecule under study and can be used to identify molecular compounds. In a complex molecular system such as an organism, tissue or cell Raman scattering occurs from all of the molecular species in the system and the result is a complex superposition of the spectra from the constituent molecules which is often still specific enough for identification.
In many samples of biological origin, laser illumination leads to luminescence, usually referred to as autofluorescence, in addition to Raman scattering. Spectroscopically this fluorescence leads to a spectrally broad background on top of which the Raman scattering is measured. This autofluorescence will often dissipate after prolonged laser exposure. A common practice is to allow a sample to “photobleach” prior to acquisition in order to increase the Raman scatter-to-background ratio and obtain a high quality Raman spectrum.
An alternative approach to reduce autofluorescence in biological samples is to illuminate with a longer wavelength laser and thus excite less autofluorescence in the sample. This is possible, however using a longer illumination wavelength has limitations of its own. Raman scattering is proportional to v4, where v is the frequency of the illuminating radiation. As the illumination is changed to longer wavelengths or lower frequency, the amount of Raman scattering decreases along with the excited autofluorescence. Raman data collection is typically performed in the visible wavelength range (˜400-700 nm) to take advantage of the increased Raman scattering of the sample.
Traditionally, trained spectroscopists decide on acquisition parameters based on their experience and the performance of the instrument and the response of the sample. The spectroscopist determines when a sample is photobleached and then determines the appropriate acquisition parameters (integration time, signal averages etc.) for the desired result. These determinations are based on the spectroscopist's expertise. A more consistent and objective approach is needed to exploit the molecular sensitivity of Raman spectroscopy in applications where users are not trained Raman experts. Automated spectral acquisition is a means of introducing consistency to data acquisition step in any application area.